The role of functional polymorphisms in immune response genes as biomarkers of BCG Immunotherapy outcome in bladder cancer: Establishment of a predictive profile in a Southern Europe population

OBJECTIVE: To evaluate the predictive value of genetic polymorphisms in the context of BCG immunotherapy outcome and create a predictive profile that may allow discriminating the risk of recurrence. MATERIAL AND METHODS: In a dataset of 204 patients treated with BCG, we evaluate 42 genetic polymorphisms in 38 genes involved in the BCG mechanism of action, using Sequenom MassARRAY technology. Stepwise multivariate Cox Regression was used for data mining. RESULTS: In agreement with previous studies we observed that gender, age, tumor multiplicity and treatment scheme were associated with BCG failure. Using stepwise multivariate Cox Regression analysis we propose the first predictive profile of BCG immunotherapy outcome and a risk score based on polymorphisms in immune system molecules (SNPs in TNFA-1031T/C (rs1799964), IL2RA rs2104286 T/C, IL17A-197G/A (rs2275913), IL17RA-809A/G (rs4819554), IL18R1 rs3771171 T/C, ICAM1 K469E (rs5498), FASL-844T/C (rs763110) and TRAILR1-397T/G (rs79037040) in association with clinicopathological variables. This risk score allows the categorization of patients into risk groups: patients within the Low Risk group have a 90% chance of successful treatment, whereas patients in the High Risk group present 75% chance of recurrence after BCG treatment. CONCLUSION: We have established the first predictive score of BCG immunotherapy outcome combining clinicopathological characteristics and a panel of genetic polymorphisms. Further studies using an independent cohort are warranted. Moreover, the inclusion of other biomarkers may help to improve the proposed model.

Predictive Biomarkers of Bacillus Calmette-Gu´erin Immunotherapy Response in Bladder Cancer: Where AreWe Now?

The most effective therapeutic option for managing nonmuscle invasive bladder cancer (NMIBC), over the last 30 years, consists of intravesical instillations with the attenuated strain Bacillus Calmette-Gu´erin (the BCG vaccine). This has been performed as an adjuvant therapeutic to transurethral resection of bladder tumour (TURBT) and mostly directed towards patients with highgrade tumours, T1 tumours, and in situ carcinomas. However, from 20% to 40% of the patients do not respond and frequently present tumour progression. Since BCG effectiveness is unpredictable, it is important to find consistent biomarkers that can aid either in the prediction of the outcome and/or side effects development. Accordingly, we conducted a systematic critical review to identify themost preeminent predictive molecular markers associated with BCG response. To the best of our knowledge, this is the first review exclusively focusing on predictive biomarkers for BCG treatment outcome. Using a specific query, 1324 abstracts were gathered, then inclusion/exclusion criteria were applied, and finally 87 manuscripts were included. Several molecules, including CD68 and genetic polymorphisms, have been identified as promising surrogate biomarkers. Combinatory analysis of the candidate predictive markers is a crucial step to create a predictive profile of treatment response.

Comparative study of 2 software programs for predicting profile changes in Class III patients having double-jaw orthognathic surgery

Introduction: Computer software can be used to predict orthognathic surgery outcomes. The aim of this study was to subjectively compare the soft-tissue surgical simulations of 2 software programs. Methods: Standard profile pictures were taken of 10 patients with a Class III malocclusion and a concave facial profile who were scheduled for double-jaw orthognathic surgery. The patients had horizontal maxillary deficiency or horizontal mandibular excess. Two software programs (Dentofacial Planner Plus [Dentofacial Software, Toronto, Ontario, Canada] and Dolphin Imaging [version 9.0, Dolphin Imaging Software, Canoga Park, Calif]) were used to predict the postsurgical profiles. The predictive images were compared with the actual final photographs. One hundred one orthodontists, oral-maxillofacial surgeons, and general dentists evaluated the images and were asked whether they would use either software program to plan treatment for, or to educate, their patients. Results: Statistical analyses showed differences between the groups when each point was judged. Dolphin Imaging software had better prediction of nasal tip, chin, and submandibular area. Dentofacial Planner Plus software was better in predicting nasolabial angle, and upper and lower lips. The total profile comparison showed no statistical difference between the softwares. Conclusions: The 2 types of software are similar for obtaining 2-dimensional predictive profile images of patients with Class III malocclusion treated with orthognathic surgery. (Am J Orthod Dentofacial Orthop 2010; 137: 452.e1-452.e5)

The critical power function is dependent on the duration of the predictive exercise tests chosen

The linear relationship between work accomplished (W-lim) and time to exhaustion (t(lim)) can be described by the equation: W-lim = a + CP.t(lim). Critical power (CP) is the slope of this line and is thought to represent a maximum rate of ATP synthesis without exhaustion, presumably an inherent characteristic of the aerobic energy system. The present investigation determined whether the choice of predictive tests would elicit significant differences in the estimated CP. Ten female physical education students completed, in random order and on consecutive days, five art-out predictive tests at preselected constant-power outputs. Predictive tests were performed on an electrically-braked cycle ergometer and power loadings were individually chosen so as to induce fatigue within approximately 1-10 mins. CP was derived by fitting the linear W-lim-t(lim) regression and calculated three ways: 1) using the first, third and fifth W-lim-t(lim) coordinates (I-135), 2) using coordinates from the three highest power outputs (I-123; mean t(lim) = 68-193 s) and 3) using coordinates from the lowest power outputs (I-345; mean t(lim) = 193-485 s). Repeated measures ANOVA revealed that CPI123 (201.0 +/- 37.9W) > CPI135 (176.1 +/- 27.6W) > CPI345 (164.0 +/- 22.8W) (P < 0.05). When the three sets of data were used to fit the hyperbolic Power-t(lim) regression, statistically significant differences between each CP were also found (P < 0.05). The shorter the predictive trials, the greater the slope of the W-lim-t(lim) regression; possibly because of the greater influence of 'aerobic inertia' on these trials. This may explain why CP has failed to represent a maximal, sustainable work rate. The present findings suggest that if CP is to represent the highest power output that an individual can maintain for a very long time without fatigue then CP should be calculated over a range of predictive tests in which the influence of aerobic inertia is minimised.

Distributed Model Predictive Control for Housing with Hourly Auction of Available Energy

This paper presents a distributed model predictive control (DMPC) for indoor thermal comfort that simultaneously optimizes the consumption of a limited shared energy resource. The control objective of each subsystem is to minimize the heating/cooling energy cost while maintaining the indoor temperature and used power inside bounds. In a distributed coordinated environment, the control uses multiple dynamically decoupled agents (one for each subsystem/house) aiming to achieve satisfaction of coupling constraints. According to the hourly power demand profile, each house assigns a priority level that indicates how much is willing to bid in auction for consume the limited clean resource. This procedure allows the bidding value vary hourly and consequently, the agents order to access to the clean energy also varies. Despite of power constraints, all houses have also thermal comfort constraints that must be fulfilled. The system is simulated with several houses in a distributed environment.

The predictive value of psychological assessment of candidates for gastric bypass: A medical chart review

Background and Objectives: Guidelines for bariatric surgery demand a psychological evaluation of applicants. The aim of this study was to evaluate if the presence of "psychological risk factors" predicts postoperative weight loss after gastric bypass. Methods: Medical records of obese women who underwent bariatric surgery between 2000 and 2004 were reviewed. Psychological assessment consisted of a one-hour semi-structured interview, summarized in a written report. Anthropometric assessment at baseline and 6,12,18 and 24 months after surgery included body weight, height and body mass index. Results: The mean BMI of included patients (N = 92) was 46.2 + 6,3 kg/m(2) (range 38.4-69.7). Based on the psychological assessment, 27% (N = 25) of the patients were classified as having "psychological risk factors" and 28% (N = 26) were diagnosed with a psychiatric diagnosis, most often major depression. Two years after gastric bypass, 16% of patients with "psychological risk factors" achieved an excellent result (%EWL > 75) versus 39% of those without (p < 0.05). About 1 out of 4 patients was in postoperative psychiatric treatment, but only half of them were identified as having "psychological risk factors" at baseline. Weight loss of patients initiating a psychiatric treatment only after surgery was less than of patients who continued psychiatric treatment already initiated before surgery (55.7 + 14.8 versus 66.5 + 14.2 %EWL). Conclusions: A single semi-structured psychological interview may identify patients who are at risk for diminished postoperative weight loss; however, psychological assessment did not identify those patients who were in need of a psychiatric postoperative treatment.

Response to Infliximab in Crohn's Disease: Genetic Analysis Supporting Expression Profile.

Substantial proportion of Crohn's disease (CD) patients shows no response or a limited response to treatment with infliximab (IFX) and to identify biomarkers of response would be of great clinical and economic benefit. The expression profile of five genes (S100A8-S100A9, G0S2, TNFAIP6, and IL11) reportedly predicted response to IFX and we aimed at investigating their etiologic role through genetic association analysis. Patients with active CD (350) who received at least three induction doses of IFX were included and classified according to IFX response. A tagging strategy was used to select genetic polymorphisms that cover the variability present in the chromosomal regions encoding the identified genes with altered expression. Following genotyping, differences between responders and nonresponders to IFX were observed in haplotypes of the studied regions: S100A8-S100A9 (rs11205276* G/rs3014866* C/rs724781* C/rs3006488* A; P = 0.05); G0S2 (rs4844486* A/rs1473683* T; P = 0.15); TNFAIP6 (rs11677200* C/rs2342910* A/rs3755480* G/rs10432475* A; P = 0.10); and IL11 (rs1126760* C/rs1042506* G; P = 0.07). These differences were amplified in patients with colonic and ileocolonic location for all but the TNFAIP6 haplotype, which evidenced significant difference in ileal CD patients. Our results support the role of the reported expression signature as predictive of anti-TNF outcome in CD patients and suggest an etiological role of those top-five genes in the IFX response pathway.

Predictive Biomarkers to Chemoradiation in Locally Advanced Rectal Cancer.

There has been a high local recurrence rate in rectal cancer. Besides improvements in surgical techniques, both neoadjuvant short-course radiotherapy and long-course chemoradiation improve oncological results. Approximately 40-60% of rectal cancer patients treated with neoadjuvant chemoradiation achieve some degree of pathologic response. However, there is no effective method of predicting which patients will respond to neoadjuvant treatment. Recent studies have evaluated the potential of genetic biomarkers to predict outcome in locally advanced rectal adenocarcinoma treated with neoadjuvant chemoradiation. The articles produced by the PubMed search were reviewed for those specifically addressing a genetic profile's ability to predict response to neoadjuvant treatment in rectal cancer. Although tissue gene microarray profiling has led to promising data in cancer, to date, none of the identified signatures or molecular markers in locally advanced rectal cancer has been successfully validated as a diagnostic or prognostic tool applicable to routine clinical practice.

The clinical profile of idiopathic and cat scratch neuroretinitis: who is at risk for recurrence?

Background: Most cases of neuroretinitis (NR) are idiopathic or due to cat scratch disease and occur as a single episode but a subgroup of patients experience recurrent attacks with cumulative visual loss. We reviewed our cases of NR to better characterize the clinical features of these subgroups in an effort to predict the risk of recurrence. Methods: Retrospective study of NR patients from a single institution. Sixty-seven patients were divided into three groups: 22 cases due to cat scratch disease (CSD-NR), 24 with idiopathic neuroretinitis (I-NR) and 21 (23 eyes) with recurrent neuroretinitis (R-NR). Results: Preceding systemic symptoms, predominantly central visual field (VF) loss and the combination of poor acuity with small relative afferent pupillary defect at presentation were common features of CSD-NR. There were no cases of recurrent CSD-NR. In the first attack of R-NR, the magnitude of VF loss at presentation was greater compared to the other two groups. While 39% of R-NR had a pattern of VF loss other than a central or cecocentral scotoma, only 13.6% of CSD-NR and 17% of I-NR showed this pattern. Visual recovery was least substantial for the R-NR group (average gain of 3.7 lines of Snellen acuity vs. 5 and 6.4 lines for CSD-NR and I-NR, respectively, and an average gain in VF score of 5.1 in the R-NR group compared to 8.2 and 11.5 for the other two groups). Conclusion: The main predictive factors for recurrence are absence of systemic symptoms, significant VF loss at presentation, particularly loss outside the central 30°, and less substantial visual recovery.

Antiretroviral drug toxicity in relation to pharmacokinetics, metabolic profile and pharmacogenetics.

Introduction: Besides therapeutic effectiveness, drug tolerability is a key issue for treatments that must be taken indefinitely. Given the high prevalence of toxicity in HIV therapy, the factors implicated in drug-induced morbidities should be identified in order to improve the safety, tolerability and adherence to the treatments. Current approaches have focused almost exclusively on parent drug concentrations; whereas recent evidence suggests that drug metabolites resulting from complex genetic and environmental influences can also contribute to treatment outcome. Pharmacogenetic variations have shown to play a relevant role in the variability observed in antiretroviral drug exposure, clinical response and sometimes toxicity. The integration of pharmacokinetic, pharmacogenetic and metabolic determinants will more probably address current therapeutic needs in patients. Areas covered: This review offers a concise description of three classes of antiretroviral drugs. The review looks at the metabolic profile of these drugs and gives a comprehensive summary of the existing literature on the influence of pharmacogenetics on their pharmacokinetics and metabolic pathways, and the associated drug or metabolite toxicity. Expert opinion: Due to the high prevalence of toxicity and the related risk of low adherence to the treatments, association of kinetic, genetic and metabolic markers predictive of therapeutic or toxicity outcomes could represent a more complete approach for optimizing antiretroviral therapy.

Interleukin-1 receptor antagonist gene (IL-1RN) polymorphism is a predictive factor of clinical pregnancy after IVF.

BACKGROUND: Only 25% of IVF transfer cycles lead to a clinical pregnancy, calling for continued technical progress but also more in depth analysis of patients' individual characteristics. The interleukin-1 (IL-1) system and matrix metalloproteinases (MMPs) are strongly implicated in embryo implantation. The genes coding for IL-1Ra (gene symbol IL-1RN), IL-1beta, MMP2 and MMP9 bear functional polymorphisms. We analysed the maternal genetic profile at these polymorphic sites in IVF patients, to determine possible correlations with IVF outcome. METHODS: One hundred and sixty women undergoing an IVF cycle were enrolled and a buccal smear was obtained. The presence of IL-1RN variable number of tandem repeats and IL-1B + 3953, MMP2-1306 and MMP9-1562 single nucleotide substitutions were determined. Patients were divided into pregnancy failures (119), biochemical pregnancies (8) and clinical pregnancies (33). RESULTS: There was a 40% decrease in IL-1RN*2 allele frequency (P = 0.024) and a 45% decrease in IL-1RN*2 carrier status in the clinical pregnancy group as compared to the pregnancy failure group (P = 0.017). This decrease was still statistically significant after a multivariate logistic regression analysis. The likelihood of a clinical pregnancy was decreased accordingly in IL-1RN*2 carriers: odds ratio = 0.349, 95% confidence interval = 0.2-0.8, P = 0.017. The IL-1B, MMP2 and MMP9 polymorphisms showed no correlation with IVF outcome. CONCLUSIONS: IL-1RN*2 allele carriage is associated with a poor prognosis of achieving a pregnancy after IVF.

Establishment and characterization of models of chemotherapy resistance in colorectal cancer: Towards a predictive signature of chemoresistance.

Current standard treatments for metastatic colorectal cancer (CRC) are based on combination regimens with one of the two chemotherapeutic drugs, irinotecan or oxaliplatin. However, drug resistance frequently limits the clinical efficacy of these therapies. In order to gain new insights into mechanisms associated with chemoresistance, and departing from three distinct CRC cell models, we generated a panel of human colorectal cancer cell lines with acquired resistance to either oxaliplatin or irinotecan. We characterized the resistant cell line variants with regards to their drug resistance profile and transcriptome, and matched our results with datasets generated from relevant clinical material to derive putative resistance biomarkers. We found that the chemoresistant cell line variants had distinctive irinotecan- or oxaliplatin-specific resistance profiles, with non-reciprocal cross-resistance. Furthermore, we could identify several new, as well as some previously described, drug resistance-associated genes for each resistant cell line variant. Each chemoresistant cell line variant acquired a unique set of changes that may represent distinct functional subtypes of chemotherapy resistance. In addition, and given the potential implications for selection of subsequent treatment, we also performed an exploratory analysis, in relevant patient cohorts, of the predictive value of each of the specific genes identified in our cellular models.

Correlation of serum leptin and insulin levels of pregnant protein-restricted rats with predictive obesity variables

During pregnancy and protein restriction, changes in serum insulin and leptin levels, food intake and several metabolic parameters normally result in enhanced adiposity. We evaluated serum leptin and insulin levels and their correlations with some predictive obesity variables in Wistar rats (90 days), up to the 14th day of pregnancy: control non-pregnant (N = 5) and pregnant (N = 7) groups (control diet: 17% protein), and low-protein non-pregnant (N = 5) and pregnant (N = 6) groups (low-protein diet: 6%). Independent of the protein content of the diet, pregnancy increased total (F1,19 = 22.28, P < 0.001) and relative (F1,19 = 5.57, P < 0.03) food intake, the variation of weight (F1,19 = 49.79, P < 0.000) and final body weight (F1,19 = 19.52, P < 0.001), but glycemia (F1,19 = 9.02, P = 0.01) and the relative weight of gonadal adipose tissue (F1,19 = 17.11, P < 0.001) were decreased. Pregnancy (F1,19 = 18.13, P < 0.001) and low-protein diet (F1,19 = 20.35, P < 0.001) increased the absolute weight of brown adipose tissue. However, the relative weight of this tissue was increased only by protein restriction (F1,19 = 15.20, P < 0.001) and the relative lipid in carcass was decreased in low-protein groups (F1,19 = 4.34, P = 0.05). Serum insulin and leptin levels were similar among groups and did not correlate with food intake. However, there was a positive relationship between serum insulin levels and carcass fat depots in low-protein groups (r = 0.37, P < 0.05), while in pregnancy serum leptin correlated with weight of gonadal (r = 0.39, P < 0.02) and retroperitoneal (r = 0.41, P < 0.01) adipose tissues. Unexpectedly, protein restriction during 14 days of pregnancy did not alter the serum profile of adiposity signals and their effects on food intake and adiposity, probably due to the short term of exposure to low-protein diet.

Predicting the profile of nutrients available for absorption: from nutrient requirement to animal response and environmental impact

Current feed evaluation systems for dairy cattle aim to match nutrient requirements with nutrient intake at pre-defined production levels. These systems were not developed to address, and are not suitable to predict, the responses to dietary changes in terms of production level and product composition, excretion of nutrients to the environment, and nutrition related disorders. The change from a requirement to a response system to meet the needs of various stakeholders requires prediction of the profile of absorbed nutrients and its subsequent utilisation for various purposes. This contribution examines the challenges to predicting the profile of nutrients available for absorption in dairy cattle and provides guidelines for further improved prediction with regard to animal production responses and environmental pollution. The profile of nutrients available for absorption comprises volatile fatty acids, long-chain fatty acids, amino acids and glucose. Thus the importance of processes in the reticulo-rumen is obvious. Much research into rumen fermentation is aimed at determination of substrate degradation rates. Quantitative knowledge on rates of passage of nutrients out of the rumen is rather limited compared with that on degradation rates, and thus should be an important theme in future research. Current systems largely ignore microbial metabolic variation, and extant mechanistic models of rumen fermentation give only limited attention to explicit representation of microbial metabolic activity. Recent molecular techniques indicate that knowledge on the presence and activity of various microbial species is far from complete. Such techniques may give a wealth of information, but to include such findings in systems predicting the nutrient profile requires close collaboration between molecular scientists and mathematical modellers on interpreting and evaluating quantitative data. Protozoal metabolism is of particular interest here given the paucity of quantitative data. Empirical models lack the biological basis necessary to evaluate mitigation strategies to reduce excretion of waste, including nitrogen, phosphorus and methane. Such models may have little predictive value when comparing various feeding strategies. Examples include the Intergovernmental Panel on Climate Change (IPCC) Tier II models to quantify methane emissions and current protein evaluation systems to evaluate low protein diets to reduce nitrogen losses to the environment. Nutrient based mechanistic models can address such issues. Since environmental issues generally attract more funding from governmental offices, further development of nutrient based models may well take place within an environmental framework.

Dynamic headspace solid-phase microextraction combined with one-dimensional gas chromatography–mass spectrometry as a powerful tool to differentiate banana cultivars based on their volatile metabolite profile

In this study the effect of the cultivar on the volatile profile of five different banana varieties was evaluated and determined by dynamic headspace solid-phase microextraction (dHS-SPME) combined with one-dimensional gas chromatography–mass spectrometry (1D-GC–qMS). This approach allowed the definition of a volatile metabolite profile to each banana variety and can be used as pertinent criteria of differentiation. The investigated banana varieties (Dwarf Cavendish, Prata, Maçã, Ouro and Platano) have certified botanical origin and belong to the Musaceae family, the most common genomic group cultivated in Madeira Island (Portugal). The influence of dHS-SPME experimental factors, namely, fibre coating, extraction time and extraction temperature, on the equilibrium headspace analysis was investigated and optimised using univariate optimisation design. A total of 68 volatile organic metabolites (VOMs) were tentatively identified and used to profile the volatile composition in different banana cultivars, thus emphasising the sensitivity and applicability of SPME for establishment of the volatile metabolomic pattern of plant secondary metabolites. Ethyl esters were found to comprise the largest chemical class accounting 80.9%, 86.5%, 51.2%, 90.1% and 6.1% of total peak area for Dwarf Cavendish, Prata, Ouro, Maçã and Platano volatile fraction, respectively. Gas chromatographic peak areas were submitted to multivariate statistical analysis (principal component and stepwise linear discriminant analysis) in order to visualise clusters within samples and to detect the volatile metabolites able to differentiate banana cultivars. The application of the multivariate analysis on the VOMs data set resulted in predictive abilities of 90% as evaluated by the cross-validation procedure.